Method and system for detecting white matter neural injury and predicting neurological outcome particularly for preterm infants

ABSTRACT

A method for detecting white matter neural injury and predicting neurological outcome for a patient, comprises acquiring EEG signal(s) from the surface of the head of the patient, and analyzing the frequency distribution or content of the signal(s) to produce output information indicative of cerebral white matter injury for the patient. Loss or reduction of activity in the upper portion or spectral edge of the EEG frequency domain particularly in the immature brain is predictive of neural dysfunction. A system for detecting white matter neural injury and predicting neurological outcome for a patient is also described.

FIELD OF INVENTION

The invention comprises a method and apparatus for detecting neuralinjuries and predicting neurological outcome. In particular theinvention is useful for detecting injuries to the immature cerebralwhite matter in preterm infants and for enabling rapid prediction of thedevelopment of subtle and severe lesions in the cerebral white matter ofand neurological outcome for preterm infants.

BACKGROUND TO THE INVENTION

Very premature infants have a markedly increased risk of neurologicalmorbidity (Volpe, Prev. Med., 23: 638-645, 1994). A recent study usingcranial ultrasonography revealed that only 2% of infants (at 23 weeks),21% (at 24 weeks) and 69% (at 25 weeks) survived without severeabnormalities (Allen et al., New Eng. J. Med, 329: 1597-1601, 1993).White matter brain damage is a characteristic of these injuries.Patterns of damage range from subtle gliosis (telencephalicleukomalacia) through to severe cystic infarctions of theperiventricular and subcortical white matter (Volpe, Prev. Med., 23:638-645, 1994).

Histopathologic studies indicate some of these lesions developprenatally, others postnatally. Poor neurological outcome is associatedwith the presence of these white matter injuries (Guit et al.,Radiology, 175: 107-109, 1990). The severe periventricular lesions arestrongly associated with cerebral palsy (Hoon, J. Perinatol., 15:389-394, 1995).

Long term neurological outcome appears to be similarly compromised. In agroup of less than 32 week old premature infants at the age of 9 years19% were in special education, 32% were in a grade below the appropriatelevel for their age and 38% required special assistance (Hille et al., JPediatr., 125: 426-434, 1994).

Similarly, another study has shown that in very premature infants about5-15% develop major spastic motor deficits and an additional 25-50%exhibit developmental and cognitive disabilities (J. J. Volpe. Braininjury in the premature infant—Current concepts of pathogenesis andprevention. Biol Neonate 62:231-242, 1992).

The aetiology of these lesions is not completely understood (Armstrong,Semin. Perinatol., 17: 342-350, 1993), but are thought to occursecondary to various prenatal environmental and genetic factors (Lou,Brain Dev., 16: 423-431, 1994).

Cerebral hypoperfusion is considered to be a significant final commonpathway in the pathogenesis of these encephalopathies (Lou, Brain Dev.,16: 423-431, 1994). Experimental and epidemiological studies generallysupport this hypothesis. For example, intrapartum acidosis and asphyxiain the premature infant carry a high risk of periventricularleukomalacia (Low et al., Am. J. Obstet. Gynaecol., 162: 977-981, 1990).Also, both increased levels of hypoxanthine and prolonged metabolicacidosis in the neonatal period are associated with a high risk ofperiventricular lesions (Russel et al., Arch. Dis. Child., 67: 388-392,1992; Low et al., Am. J. Obstet. Gynaecol., 162: 977-981, 1990). Inparticular, periventricular lesions are probably caused by cerebralhypoxia-ischaemia following arterial hypotension (Iida et al., Pediatr.Neurol., 8: 205-209, 1992). Cerebral hypoxia-ischaemia may arise fromproblems associated with prematurity including respiratory distresssyndrome, patent ductus arteriosis, necrotizing enterocolitis andsepsis. There is considerable variation in the pattern of lesionsobserved and a range of factors are likely to influence outcome,including gestational age and the severity and nature of the insult(Gluckman et al., Proceedings of The Alfred Benzon Symposium no. 37,Munksgaard, Copenhagen, 1993). Other factors such as hypoglycaemia,infections or toxaemia are also likely to be important (Piekkala et al.,Early Hum. Dev., 13: 249-268, 1986).

Current methods for assessing brain injury reveal damaged areas of thebrain, but do not identify those premature infants at risk of sufferinga neural injury. Brain damage assessed by neurological examination is oflimited prognostic value, especially for those preterm infants on lifesupport. Ultrasonography is also used and reveals lesions as whitematter echodensities and echoluciencies, which are useful in predictingfuture handicap, such as cerebral palsy. However, this approach is lesssuitable for monitoring and detecting pathophysiologic events which mayoccur over several days, the knowledge of which could be used tominimise or avoid further injury.

Greater reliance needs to be placed on other investigations such aspathophysiologic measures (Hill, Clin. Invest. Med., 16: 141-148, 1993).Doppler cerebral haemodynamic measures have not been proven to bepredictive of outcome (Shortland et al., J. Perinat. Med., 18: 411-417,1990). In the more mature brain the EEG signal can be used to predictsevere loss of the superficial neurons that generate this signal(Williams et al Ann Neurol, 31:14-21 1992).

Two patterns of white matter damage can occur: ‘subtle’ white matterdamage which manifests as gliosis, impaired myelination,ventriculomegaly and is often termed telencephalic leucomalacia;‘severe’ cystic infarctions within the perventricular and subcorticalwhite matter. The former are associated with cognitive deficits and thelatter lesions are strongly associated with cerebral palsy.

Histopathological studies indicate the timing of injury is variable—somemay develop prenatally whereas many others appear to develop during thefirst postnatal weeks. However in surviving infants the timing ofinjuries is typically unclear and there are considerable problems withdetecting when these white matter injuries occur (D. J. Murphy, M. V.Squier, P. L. Hope, S. Sellers and A. Johnson. Clinical associations andtime of onset of cerebral white matter damage in very preterm babies.Arch Dis Child Fetal Neonat Ed 75 (1 Special Issue SI):F 27-F 32, 1996).The inability to detect the onset of injury makes management difficult.For example, if a subtle or severe injury to the deep white matter couldbe rapidly detected, then the injurious factor could be corrected ortreatment applied.

SUMMARY OF THE INVENTION

The invention provides a method and system for detecting white matterneural injury and predicting neurological outcome particularly inpreterm infants.

In broad terms in one aspect the invention comprises a method fordetecting white matter neural injury and predicting neurological outcomefor a patient, comprising:

acquiring EEG signal(s) from the surface of the head of the patient, and

analysing the frequency distribution of the signal(s) to produce outputinformation indicative of cerebral white matter injury for the patient.

Preferably the method includes comparing the analysed data with storedcomparative spectral edge and neurological outcome information toproduce information useful for managing the patient.

In broad terms in another aspect the invention comprises a system fordetecting neural injury and predicting neurological outcome for apatient, comprising:

means for acquiring EEG signal(s) from the surface of the head of apatient, and

computing means arranged to analyse the frequency distribution of theEEG signals to produce output information indicative of cerebral whitematter injury for the patient.

An electroencephalogram or EEG provides a record of electrical activityfrom the most superficial layers of the cerebral cortex recorded fromelectrodes on the scalp. This activity is the result of the rhythmicdischarging of neurons under the electrode. The EEG signal providesinformation about the frequency and amplitude of the neuronal electricalactivity and its temporal variation. We have found experimentally thatloss of spectral edge frequency is highly predictive of deep whitematter damage in the preterm foetus. By preterm or premature is meantinfants born at less than 37 weeks gestation. The method and system ofthe invention also have application in detecting white matter neuralinjury in child and adult patients however.

DESCRIPTION OF FIGURES

The invention is further described with reference to the accompanyingfigures in which:

FIG. 1 is an overview of one form of system of the invention,

FIG. 2 is a schematic horizontal cross-sectional diagram of the brainshowing where white matter injuries develop and the optimum placement ofthe EEG electrodes on each hemisphere for the detection of theseinjuries,

FIGS. 3a and 3 b are graphs of EEG spectral edge frequency recordingsfor human infants: FIG. 3a is a recording from a normal infant and FIG.3b is a recording from an infant with cystic white matter lesions,

FIGS. 4a, 4 b and 4 c are graphs of cortical impedance for the preterm(0.65 gestation) foetal sheep over an 80 hour period following a 15,22.5 and 30 minute cerebral hypoperfusion injury respectively,

FIGS. 5a, 5 b and 5 c are graphs of EEG spectral edge frequency over thesame 80 hour period,

FIGS. 6a, 6 b and 6 c show EEG intensity taken over the same 80 hourperiod,

FIGS. 7a, 7 b and 7 c show the cortical impedance, EEG intensity, andspectral edge frequency plots each on the same axes, showing that thedistinctive frequency response can be used to detect subtle (22.5 min)and severe white matter injuries (30 min),

FIG. 8 is a graph comparing the density of GFAP positive cells in thesubcortical white matter following different durations of ischemicinjury,

FIG. 9 is a graph comparing the density of TUNEL positive cells in thesubcortical white matter following the same different durations ofischemic injury, and

FIGS. 10a and 10 b are illustrations of the diffuse glial (GFAP)reaction in the white matter of the parietal cortex following the 22.5minutes of ischemia injury and from an age matched control,respectively.

DETAILED DESCRIPTION

As stated we have found that a lowering of the frequency distribution ofthe EEG activity, measured by a fall in spectral edge frequency of theEEG signals, is indicative of cerebral white matter injury. Typicallythe EEG frequency spectrum comprises signals in a 1 to 20 Hz range, withmost activity between about 1 and 15 Hz. In the method and system of theinvention, the EEG signals are analysed to determine the proportion ofthe intensity spectrum in the top 50%, preferably the top 30%, morepreferably the top 10%, and most preferably the top 5% of the frequencyrange, and a reduction in this spectral edge frequency is indicative ofcerebral white matter both subtle and severe white matter injuries andlong term neurological outcome. FIG. 3a shows EEG spectral edgerecording for a normal human infant, with EEG activity up to about 15Hz. FIG. 3b shows EEG spectral edge recording for an infant withcerebral white matter cystic lesions, in which there was a loss offrequency with spectral edge activity above about 10 Hz. Thesedistinctive frequency responses are similar to those that were observedin the preterm fetal sheep.

FIG. 2 is a schematic horizontal cross-sectional diagram of a preterminfant's brain showing the vulnerable developing white matter regionsdorsal and lateral to the lateral ventricles. These regions may suffer‘subtle’ injuries where gliosis occurs or develop more severe cysticlesions. Note that the overlying grey matter or neurons are typicallyspared from these injuries. FIG. 2 also shows the preferred EEGelectrode placement with the system and method of the invention. Auseful site is to record from the parasagittalregion/fronto-parietal-occipital cortex that overlies the region wherethe white matter injury may develop as indicated in FIG. 2.

In the method and system of the invention a suitable conventionalelectrode, amplifier and patient isolation system is used to acquire EEGsignals from the head of a subject patient such as an infant, which arethen analysed in computing means comprising signal analysis softwarearranged to examine the upper portions or spectral edge of the frequencydomain of the EEG signals, and to output the analysis as informationindicative of neural injury and neurological outcome for the subjectinfant.

The system hardware may take any suitable form such as a personalcomputer including a dedicated data acquisition board to which a numberof EEG electrodes are connected, the computer screen displaying theanalysis graphically and/or as text. In another form an otherwiseconventional EEG system may be arranged to process acquired EEG signalsand analyse the signals according to the method of the invention, as asignal processing option on the EEG machine, and display and/or printthe results. In a further form a system of the invention may comprise asmaller dedicated apparatus or instrument including EEG signalacquisition equipment, a computer section comprising an embeddedmicroprocessor, data analysis software, and a display. In each case theresults of the analysis may be displayed or printed for interpretationby a physician, or may be further processed against stored comparativeinformation and displayed or printed in a form which is predictive ofneurological outcome of the subject infant.

The EEG signals may be acquired from electrodes placed on the infant'shead over the parasagittal region/fronto-parietal-occipital cortex. Theymay be acquired over a number of hours, or over one or more days, andmay be averaged over such periods. They may be analyzed in the frequencydomain for loss of EEG activity above about 10 Hz, or above about 8 Hz.

FIG. 1 schematically illustrates one form of system of the invention. Aset of EEG leads are applied to the head 100 of an infant as shown at101. The EEG signals are filtered as necessary, amplified, andanalogue-to-digital converted in block 104 and passed to data buffer105. The digitised input signals data may also be compressed and stored.Data compression may involve averaging or time-to-frequency domainconversion. Standard computer-compatible data storage devices with astandard system for file naming and configuration may be utilised.

The intensity spectrum of the EEG signals in the frequency domain isobtained using fast Fourier transform techniques (FFT) or any othersignal processing technique which enables the frequency content of theEEG signals to be examined and measures of the frequency distributionsuch as spectral edge frequency to be calculated. The preferred formsystem is arranged to carry out this analysis in the signal analysismodule 106. The results may then be displayed for interpretation by aphysician, but preferably the current and stored data for the patientmay be analysed against stored comparative information on spectral edgefrequency versus likely neurological outcome and analytical rulesindicated by block 108, in expert analysis module 107 and the resultsdisplayed.

Optionally the system may make available expert advice having an inbuiltability to predict outcome and/or to identify the pathological processestaking place through an advisor/help system. The system may also makeavailable representative examples of pathophysiologic reactions whichcan be called up by a user contemplating the case under study.

Once a loss of EEG activity in the upper part of the frequency range inan infant is detected by the system and method of this invention,therapy against the development of white matter injury may be applied tothe infant.

FIG. 1 also comprises a dataflow diagram and illustrates that digitalsignals are fed continuously into input data buffer 105, subsequentlythrough the signal analysis module 106, and then through the expertanalysis module 107, and to the display, or data storage device(s). Thesignal analysis module also performs artefact rejection, and datareduction.

User interaction with and control of the system in the preferred formsystem may be via a touch sensitive screen or a touch panel or keypad109, on the front face of an instrument for example, a keyboard and/or amouse, a separate hand held infra-red unit, or other convenient form ofinput device. The unit may include a printer port 113 or a built-inprinter, or a network interface. Preferably the system is capable ofstoring and recalling data over a period of for example 3 days or more.

Preferably the system monitors each signal line in order to confirm thateach channel continues to provide reliable results because (for example)attached electrodes can be detached or lose effectiveness in other ways.In the event of a problem the corresponding data is disregarded and awarning message is generated, and the system may also indicate to theuser any detached or ineffective electrode.

The following description of experimental work further assistsunderstanding of the invention:

Experimental

In order to determine if any biophysical parameters were useful fordetecting injuries within the immature white matter the followinginvestigations were performed. Preterm 0.65 gestation foetal sheep weresubjected to cerebral hypoperfusion injury for 15, 22.5 and 30 minutes.The cortical EEG and impedance of the foetal sheep was continuouslyrecorded and the white matter analysed by histopathological methods forthe presence of injury. At this gestational age, neurogenesis is largelycomplete (Barlow Russell McVeagh 1969 The foetal sheep: Morphogenesis ofthe nervous system and histochemical aspects of myelination. J CompNeurol 135:249-262 Patterson D S P, Sweasey D, Herbert C N 1971 Changesoccurring in the chemical composition of the central nervous systemduring foetal and post-natal development of the sheep. J Neurochem18:2027-2040, and the cerebral sulci begin to develop and in man thisoccurs between 26 and 28 weeks. The cortical component of auditory andsomatosensory evoked response becomes detectable at around 0.7gestation, where as in man this occurs approximately 28 weeks ofgestation (Hrbek A, Karlsson K, Kjellmer I, Olsson T, Riha M 1974Cerebral reactions during intrauterine asphyxia in the sheep. II. Evokedelectroencephalogram responses. Pediatr Res 8:58-63, Cook C J, WilliamsC E, Gluckman P D 1987 Brainstem auditory evoked potentials in the fetallamb, in utero. J Dev Physiol 9:429-440. Cook C J, Gluckman P D,Johnston B M, Williams C E 1987 The development of the somatosensoryevoked potential in the unanaesthetised fetal lamb. J Dev Physiol9:441-456). Thus in terms of neural maturation the 0.65 gestation fetalsheep is highly comparable to the human between 24 and 32 weeks ofgestation. During the 15 minute cerebral hypoperfusion injury an acuterise in cortical impedance (a measure of cytotoxic oedema) was measured,and a loss of spectral edge frequency in the EEG signal was observed—seeFIGS. 1a, 2 a and 4. In FIG. 2 100% on the vertical axis representsnormal spectral edge frequency and amplitude. These features rapidlyresolved after the hypoperfusion injury.

Following the 22.5 minute injury, there was a prolonged decrease in EEGspectral edge frequency—see FIGS. 4b, 5 b and 7. Subsequentlyhistopathologic analysis of the brain material showed gliosis in thecorpus callosum and subcortical white matter which extended from theperiventricular region dorsally and laterally. An equivalent type of‘subtle’ injury is found in human infants, called telencephalicleukomalacia. The neurological outcome from this type of injury inhumans is poor (Fujii et al., Pediatr Neurol., 9, 194-197, 1993). Webelieve that this loss of EEG spectral edge frequency is indicative ofwhite matter injury.

Following the 30 minute injury a secondary rise in impedance occurredwith nonrecovery of spectral edge associated with severe white mattercystic infarction see FIGS. 4c, 6 c and 7. Spectral edge activity in theEEG signal was permanently reduced to only around 50% of normal—see FIG.5c. We believe this long term loss of spectral edge frequency isindicative of low long term neurological outcome. The term given to theequivalent type of white matter injury in the human infants isperiventricular leukomalacia.

FIGS. 6a, 6 b and 6 c show a transient loss of EEG intensity in eachcase. At the onset of diminished blood perfusion there was a rapid lossof EEG intensity and while the recovery time to return to pre-injury EEGintensity was longer in the 30 minute injury compared with the 15 minuteinjury, the final outcome for the 3 durations of injury was the same.

FIG. 7 clearly demonstrates that both white matter gliosis and cysticinfarction was associated with a prolonged loss of EEG frequency asindicated by the spectral edge data. In contrast the measures of theintensity (or similar measures such as power or amplitude) of the EEGwere much less useful for detecting these white matter injuriesfollowing an insult.

FIG. 8 is a graph comparing the density of GFAP positive cells in thesubcortical white matter following different durations of ischemicinjury. The density of these cells was determined in the frontoparietalcortex dorsolateral to the external angle of the lateral ventricle.There was only a mild (non significant) response in the 15 minute group.There was a marked increase in the number of GFAP positive cells in the22.5 minute group (p<0.05). After the 30 minute injury, the GFAPresponse was less than the 22.5 minute group. This lesser induction inthe 30 min group reflects the presence of extensive cell death withinthe same region. Kruskall Wallis ANOVA on ranks. The marked increase inthe number of cells (GFAP) after the 22.5 min injury is indicative of a‘subtle’ injury to the white matter tracts.

FIG. 9 is a graph comparing the density of TUNEL positive cells in thesubcortical white matter following the different durations of ischemicinjury. The density of these cells was determined in the region dorsaland lateral to the external angle of the lateral ventricle. There was asignificant increase of TUNEL positive cells only after the 30 minuteinjury. This cell loss reflects the development of a severe or cysticwhite matter lesion.

FIGS. 10 and 10b are illustrations of representative examples of thediffuse glial (GFAP) reaction in the white matter of the parietal cortexfollowing the 22.5 minutes of ischemia injury and from an age matchedcontrol. Note that the GFAP positive cells in the 22.5 minute group havea morphology typical of hypertrophic or reactive astrocytes (lowerleft). Brown stain is GFAP immunoreactivity. Bar=100 μm. This reactionis typical of a ‘subtle’ white matter injury.

Thus, we believe that loss or reduction of activity in the upper portionor spectral edge of the EEG frequency domain particularly in theimmature brain is predictive of neural dysfunction, while EEG intensityis not. Furthermore, nonrecovery of spectral edge frequency ispredictive of the type of neural injury that has occurred.

The foregoing describes the invention including preferred forms thereof.Alterations and modifications as will be obvious to those skilled in theart are intended to be incorporated within the scope hereof as definedin the claims.

What is claimed is:
 1. A method for early prediction of neural damage orneurological outcome for an infant born prematurely, comprising:acquiring EEG signal(s) from the surface of the head of the infant,analysing the frequency distribution or content of the signal(s) todetermine the frequency range in which a major portion of the EEGactivity in the frequency domain occurs or a frequency below which amajor portion of the EEG activity occurs, and predicting neural damageor neurological outcome for the infant based on EEG activity or lossthereof in the upper part of the frequency range.
 2. A method accordingto claim 1 including comparing the analysed data with stored comparativespectral edge and neurological outcome information for infants bornprematurely.
 3. A method according to claim 1 including acquiring theEEG signal(s) over a number of hours.
 4. A method according to claim 1including acquiring the EEG signal(s) over one or more days.
 5. A methodaccording to claim 1 including averaging the EEG signal(s) acquired overa number of hours or one or more days.
 6. A method according to claim 1including analysing the EEG signals in the frequency domain for loss ofEEG activity above about 10 Hz.
 7. A method according to claim 1including analysing the EEG signals in the frequency domain for loss ofEEG activity above about 8 Hz.
 8. A method according to claim 1including determining the frequency below which about 90% of the EEGactivity in the frequency domain occurs.
 9. A method according to claim1 including determining the frequency below which about 95% of the EEGactivity in the frequency domain occurs.
 10. A method according to claim1 wherein the EEG signals are acquired from electrodes placed on theinfants head over the parasagittal region/fronto-parietal-occipitalcortex.
 11. A method according to claim 1 including applying to theinfant therapy against the development of white matter injury afterdetecting any loss of EEG activity in the upper part of the frequencyrange.
 12. A method according to claim 1 wherein said neural damage istelencephalic leukomalacia or periventricular leukomalacia.
 13. A systemfor early prediction of neural injury or neurological outcome for aninfant born prematurely, comprising: means for acquiring EEG signal(s)from the surface of the head of the infant, and computing means arrangedto analyse the frequency distribution or content of the signal(s) todetermine the frequency range in which a major portion of the EEGactivity in the frequency domain occurs or a frequency below which amajor portion of the EEG activity occurs, and to compare the analyseddata with stored comparative EEG frequency and neural damage orneurological outcome information for infants born prematurely andproduce output information predictive of neural damage or neurologicaloutcome for the infant based on EEG activity or loss thereof in theupper part of the frequency range.
 14. A system according to claim 13arranged to analyse EEG signal(s) acquired over a number of hours.
 15. Asystem according to claim 13 arranged to analyse EEG signal(s) acquiredover one or more days.
 16. A system according to claim 14 arranged toaverage the EEG signal(s) acquired over a number of hours or one or moredays.
 17. A system according to claim 13 arranged to analyse the EEGsignals in the frequency domain for activity above 10 Hz.
 18. A systemaccording to claim 13 arranged to analyse the EEG signals in thefrequency domain for activity above 8 Hz.
 19. A system according toclaim 13 to arranged to determine the frequency below which about 90% ofthe EEG activity in the frequency domain occurs.
 20. A system accordingto claim 13 arranged to determine the frequency below which about 95% ofthe EEG activity in the frequency domain occurs.